1. Field of the Invention
The present invention relates to an image recognition technique, and in particular relates to an image matching technique for judging whether two plane images match.
2. Description of the Related Art
With rapid developments in hardware and software technologies in recent years, high-volume image data has become widely used in information processing.
For instance, an image database made up of considerable amounts of image data and managed under a database management system is used in various fields, such as medical care, office works, and scientific researches.
For instance, an image database made up of considerable amounts of image data and managed under a database management system is used in various fields, such as medical care, office work, and scientific research.
The last mentioned comparison method can also be applied to recognition of a captured image, by using the captured image as the retrieval key and searching the image database for an image that matches the captured image.
The following is an explanation of a conventional image matching technique used for the above comparison method.
FIGS. 1A and 1B are a conceptual diagram showing image matching in the conventional technique.
Images 901, 902, and 903 are each made up of 32.times.32 sets of pixel data, while a part of pixel data which compose image 901 is enlarged in image 910. Here, the sets of pixel data that make up each of the images have an 8-step monochrome graduation and therefore the actual images should be delivered in shades of gray, though the gray levels of the images are omitted in FIG. 1. A value assigned to each set of pixel data represents an intensity level of the pixel.
When images 902 and 903 are stored in an image database and image 901 is used as a retrieval key, image matching is performed as follows.
To compare image 901 with image 902 using the conventional image matching technique, the following calculation is performed for sets of pixel data C.sub.1, C.sub.2, C.sub.3, . . . , C.sub.1024 which make up image 901 and sets of pixel data D.sub.1, D.sub.2, D.sub.3, . . . , D.sub.1024 which make up image 902. EQU .eta.=(.SIGMA.C.sub.j.multidot.D.sub.j)/(.SIGMA.C.sub.j.sup. 2.multidot..SIGMA.D.sub.j.sup.2) [j=1.about.1024]
When .eta. approximates to 1, it is judged that images 901 and 902 match.
The same calculation is performed to compare image 901 with image 903.
However, when an image has been captured using scaling and rotation, such a image is not congruent with but is merely similar to the other image with which the image is to be compared.
FIG. 2 shows two images 911 and 902 that differ in sizes and orientations.
To compare image 911 with image 902 using the conventional image matching technique, scaling and rotation have to be repeatedly performed on image 911 to judge whether image 911 matches image 902, that is, whether the object in image 911 is identical to the object in image 902.